This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Fluoroacetate dehalogenases catalyze the hydrolysis of fluoroacetate into glycolate. They possess the rare ability of breaking the carbon-fluorine bond, the strongest bond in organic chemistry. They are thus promising candidates in the bioremediation of some of the most persistent environmental contaminants. We are interested in understanding how the defluorinases function at the atomic level to gain valuable insights for developing solutions for degrading fluorinated organic pollutants. Traditionally, the structural characterization of enzymatic function, or structural enzymology, is performed using various trapping strategies. While countless reaction mechanisms have been elucidated by such means, these methods suffer from potentially introducing artifacts such as non-physiologically relevant binding modes in mutant enzymes. Therefore, we propose to use time-resolved crystallography (TRX) to study the enzymatic cleavage of the C-F bond;TRX is a very powerful tool in structural enzymology because it does not involve any trapping of reaction intermediates. More significantly, it has the capability of identifying some extremely short-lived structural intermediates (sub-ns timescale) which is not easily achievable by other means. Despite these advantages, TRX is not readily applicable in structural enzymology. Firstly, a fast method of triggering the reaction (often involving a laser pulse) must be available;this is by far the biggest limitation of TRX. For studying irreversible reactions, the requirements become even more demanding because the relatively slow read-out times of current CCD detectors (~ 3 s) would necessitate thousands of protein crystals. Obviously, this is prohibitively excessive from the practical point of view. Fortunately, a novel data collection strategy developed by Dr. Zhong Ren (BioCARS, APS) promises to reduce this requirement by an order of magnitude.